A graph-based workflow for extracting grain-scale toughness from meso-scale experiments

•A novel machine learning computational framework that computes meso- and micro-scale material toughness is introduced.•The framework achieves high accuracy predictions after being trained on a synthetic dataset.•Performance enhancement to different microstructures is achieved with limited additional training.•The limited additional training enables implementation of this computational tool to experimental measurements.